Is there any literature on the design of dialogue systems for interviews and questionnaire administration?
[Disclaimer: I work for a company that provides a platform for developing conversational AI systems]

The platform used by the company I work for has a sentiment analysis component, so you can recognise if the user input expresses certain emotions. The dialogues are encoded in 'flows', which are graphs with an initial trigger consisting of output nodes and transitions that correspond to user input. In order to react to emotions expressed by the user you'd have a trigger that does not react to the user input text, but instead to a setting of the sentiment flags.

For example, in a call centre bot, if the user repeatedly uses angry sentiment in their utterances, the bot could detect this and trigger a flow that says "It seems you are not happy with my responses -- please wait while I transfer you to a human agent".

This all depends on the mechanics of organising the dialogues. If you have a ML model, this will probably not be as easy as if you have a manually designed graph structure (which gives you more control over such matters).

Being a commercial system, there are obviously no academic papers on this. But as it's so easy to do within the platform, it doesn't seem too much of a problem in the first place.